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All Journal Mechatronics, Electrical Power, and Vehicular Technology
Baskoro, Catur Hilman Adritya Haryo Bhakti
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Electrical & Electronics Engineering

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Journal : Mechatronics, Electrical Power, and Vehicular Technology

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An open-source parallel gripper with an embedded soft skin fingertip sensor Arifin, Muhammad; Pratama, Rian Putra; Mahendra, Oka; Munandar, Aris; Baskoro, Catur Hilman Adritya Haryo Bhakti; Muhtadin, Muhtadin; Iskandar, Abdullah
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 2 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.114-126

Abstract

The demand for implementing robots into our daily lives has surged in recent years, necessitating safe grasping for effective interaction with the environment. However, a majority of researchers rely on commercial grippers for their experimental studies, which are typically expensive and not accessible to everyone. Despite the existence of open-source designs, the assembly process is often challenging and requires modifications to enhance secure grasping. This paper presents a simple, compact, and low-cost gripper to offer an accessible and readily deployable solution for research and education. The gripper utilizes a parallel four-bar linkage mechanism, minimizing the number of components and incorporating off-the-shelf parts for straightforward assembly. Furthermore, to enhance its capabilities, the proposed gripper implements a soft skin tactile sensor on its fingertips. These sensors offer three-directional measurements using Hall effect sensing and embedded silicone. By controlling fingertip force based on information from the tactile sensors, the gripper achieves safe grasping. The gripper is evaluated to grasp daily life objects with different properties such as shapes, sizes, and levels of deformability. Evaluation results showcase the gripper's versatility, enabling it to securely grasp various objects, including fragile items. This outcome underscores the gripper's effectiveness, versatility, and safety in practical use.
Design of switched reluctance motor as actuator in an end-effector-based wrist rehabilitation robot Azhari, Budi; Hikmawan, Muhammad Fathul; Nugraha, Aditya Sukma; Yazid, Edwar; Pakha, Aji Nasirohman; Baskoro, Catur Hilman Adritya Haryo Bhakti; Rahmat, Rahmat; Ramadiansyah, Mohamad Luthfi
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.1109

Abstract

The non-communicable diseases have become the top cause of global mortality. One of them is stroke, which also become the first cause of disability worldwide. To help rehabilitate the upper extremities function of stroke survivors, a rehabilitation aid robot is developed, also to bridge the gap between patient and medical staff numbers. An end-effector-based rehabilitation robot is one proposed device. In this case, a switched reluctance motor (SRM) can be utilized as the actuator for its simplicity, robustness, high low-speed torque, and low cost. Thus, this paper proposes a design of SRM to be used as the actuator of an end-effector-based wrist rehabilitation robot. The proposed design is made based on the required torque. To extract the outputs, calculation and simulation using finite element magnetic FEMM 4.2 are conducted. The results show that the SRM produces enough torque, according to references. Moreover, rotor tooth width reduction is not preferred, as it increases the negative torque even though it raises the saliency ratio and cuts the mass of the motor.
Three-axis flexible tube sensor with LSTM-based force prediction for alignment of electric vehicle charging ports Saputra, Hendri Maja; Pahrurrozi, Ahmad; Baskoro, Catur Hilman Adritya Haryo Bhakti; Nor, Nur Safwati Mohd; Ismail, Nanang; Rijanto, Estiko; Yazid, Edwar; Zain, Mohd Zarhamdy Md; Darus, Intan Zaurah Mat
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.1104

Abstract

This paper introduces a novel three-axis flexible tube sensor designed for force measurement in electric vehicle (EV) charging port alignment, utilizing long short-term memory (LSTM) networks. The research aims to develop and validate a flexible and accurate sensor system capable of predicting multi-axis forces during alignment. The sensor integrates a magnetic sensor at the center of a flexible tube to capture three-dimensional (3-D) magnetic field variations corresponding to force changes. Fabricated using thermoplastic polyurethane (TPU) via 3-D printing technology, the sensor leverages machine learning to predict force values along the , , and  axes ( , , ). Finite element method (FEM) analysis was conducted to assess the deflection characteristics of the flexible tube under various force conditions. Experimental results demonstrate that integrating LSTM significantly enhances the accuracy of force prediction, achieving an R² score exceeding 97 % for all axes, with mean squared error (MSE) values of 0.2819 for the -axis, 0.3567 for the -axis, and 2.8086 for the -axis. The sensor is capable of measuring forces up to 30 N without exceeding its elastic limits. These findings highlight the sensor’s potential for improving alignment accuracy and reliability in automated EV charging systems.
Non-linear model predictive control with single-shooting method for autonomous personal mobility vehicle Pratama, Rakha Rahmadani; Baskoro, Catur Hilman Adritya Haryo Bhakti; Setiawan, Joga Dharma; Dewi, Dyah Kusuma; Paryanto, Paryanto; Ariyanto, Mochammad; Saputra, Roni Permana
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.1105

Abstract

The advancement of autonomous vehicle technology has markedly evolved during the last decades. Reliable vehicle control is one of the essential technologies in this domain. This study aims to develop a proposed method for controlling an autonomous personal mobility vehicle called SEATER (Single-passenger Electric Autonomous Transporter), using Non-linear Model Predictive Control (NMPC). We propose a single-shooting technique to solve the optimal control problem (OCP) via non-linear programming (NLP). The NMPC is applied to a non-holonomic vehicle with a differential drive setup. The vehicle utilizes odometry data as feedback to help guide it to its target position while complying with constraints, such as vehicle constraints and avoiding obstacles. To evaluate the method's performance, we have developed the SEATER model and testing environment in the Gazebo Simulation and implemented the NMPC via the Robot Operating System (ROS) framework. Several simulations have been done in both obstacle-free and obstacle-filled areas. Based on the simulation results, the NMPC approach effectively directed the vehicle to the desired pose while satisfying the set constraints. In addition, the results from this study have also pointed out the reliability and real-time performance of NMPC with a single-shooting method for controlling SEATER in the various tested scenarios.
Co-Authors Aris Munandar Budi Azhari Darus, Intan Zaurah Mat Dyah Kusuma Dewi Edwar Yazid Estiko Rijanto Hendri Maja Saputra Hikmawan, Muhammad Fathul Iskandar, Abdullah Joga Dharma Setiawan Mochammad Ariyanto Muhtadin Muhtadin Nanang Ismail Nor, Nur Safwati Mohd Oka Mahendra Pahrurrozi, Ahmad Pakha, Aji Nasirohman Paryanto Paryanto Pratama, Rakha Rahmadani Pratama, Rian Putra Rahmat Rahmat Ramadiansyah, Mohamad Luthfi Roni Permana Saputra Sukma Aditya Tamaulina Br Sembiring Zain, Mohd Zarhamdy Md